624 high-performance-computing-"https:"-"CIPMM---Systemic-Neurophysiology" PhD positions
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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supportive international research environment with English as the primary working language Access to state-of-the-art infrastructure and high-performance computing Dedicated training programs to enhance your
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collaboration with a leading high-tech semiconductor manufacturing company, demonstrating how edge devices can execute foundation models with guaranteed performance and minimal energy footprint—closing the gap
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problems. Use the measurement / test data to identify the high-fidelity modelling parameters by solving the inverse problem. Validate the digital model against test scenarios. Perform what-if analyses
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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quantification, and high-performance computing, with applications in the natural and engineering sciences. The position also includes teaching responsibilities equivalent to 4 contact hours per week, as
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(UTC) Country Germany Type of Contract To be defined Job Status Other Offer Starting Date 22 Jan 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the
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gas analysis, a GC/MS, and an HPLC/MS. DFT calculations will be performed using annual allocations on national high-performance computing centers. More details here: https://iramis.cea.fr/en/nimbe/lcmce
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) Country Belgium Type of Contract To be defined Job Status Full-time Offer Starting Date 21 Apr 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference
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the Research Training Group "AirMetro - Technological & Operational Integration of Highly Automated Air Transport in Urban Areas" (RTG 2947) , funded by the German Research Foundation (DFG